MEMIDP
MEMIDP, short for "Memory-Efficient Multi-Instance Deep Learning Platform," is an open-source framework designed to optimize deep learning workflows for environments with limited computational resources. It focuses on reducing memory overhead while enabling efficient training and inference across multiple deep learning models simultaneously. MEMIDP is particularly useful in scenarios where hardware constraints, such as limited GPU memory, restrict the ability to run large-scale models or batch processing.
The platform leverages several key techniques to enhance memory efficiency. One of its primary features is
MEMIDP supports a wide range of deep learning architectures, including convolutional neural networks (CNNs), recurrent neural
Developed with scalability in mind, MEMIDP is suitable for both research and production environments. It is
MEMIDP is actively maintained by a community of developers and researchers, with ongoing improvements aimed at